Customer profiling that accounts for early product programs

ABSTRACT

Aspects include identifying a customer that received a product as part of an early product program. A document that describes the early product program is accessed. Variables of the early product program are extracted based at least in part on content of the document. Customer profile rules are created based at least in part on the extracted variables. The customer profile rules are applied to a customer profile of the customer. The applying includes identifying issues in the customer profile of the customer that relate to the early product program. The customer profile of the customer is updated based at least in part on the applying. The updating includes flagging the identified issues as being related to the early product program.

BACKGROUND

Embodiments of the present invention relate in general to customerprofiling, and more specifically to customer profiling that accounts forearly product programs.

Special agreement programs between a product manufacturer and a set ofselected customers are often used in industries which require customertesting of products. Early product programs can be in place forcustomers who are willing to use a product before it becomes generallyavailable to the public. An example of an early product program is abeta program for computer software. Beta software typically is softwarethat is considered complete but still not ready for general use due toits lack of testing at customer locations. Beta software is oftendistributed to selected customers to install for use at customerlocations so that they can test and provide feedback about the product.Special agreement programs can also be in place during new featuredeployment where, for example, selected customers are installing a patchor new feature before it is available to other customers.

SUMMARY

Embodiments of the present invention include methods, systems, andcomputer program products for customer profiling that accounts for earlyproduct programs. A non-limiting example method includes identifying acustomer that received a product as part of an early product program andaccessing a document that describes the early product program. Variablesof the early product program are extracted based at least in part oncontent of the document. Customer profile rules are created based atleast in part on the extracted variables. The customer profile rules areapplied to a customer profile of the customer. The applying includesidentifying issues in the customer profile of the customer that relateto the early product program. The customer profile of the customer isupdated based at least in part on the applying. The updating includesflagging the identified issues as being related to the early productprogram.

Additional features and advantages are realized through the techniquesof the present invention. Other embodiments and aspects of the inventionare described in detail herein and are considered a part of the claimedinvention. For a better understanding of the invention with theadvantages and the features, refer to the description and to thedrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The specifics of the exclusive rights described herein are particularlypointed out and distinctly claimed in the claims at the conclusion ofthe specification. The foregoing and other features and advantages ofthe embodiments of the invention are apparent from the followingdetailed description taken in conjunction with the accompanying drawingsin which:

FIG. 1 depicts a block diagram of issues identified in a customerprofile of a customer who has participated in an early product programin accordance with one or more embodiments of the present invention;

FIG. 2 depicts a block diagram of a computer system for customerprofiling that accounts for early product programs in accordance withone or more embodiments of the present invention;

FIG. 3 depicts a flow diagram for customer profiling that accounts forearly product programs in accordance with one or more embodiments of thepresent invention; and

FIG. 4 depicts a block diagram of a computer system for implementingsome or all aspects of customer profiling that accounts for earlyproduct programs in accordance with one or more embodiments of thepresent invention.

The diagrams depicted herein are illustrative. There can be manyvariations to the diagram or the operations described therein withoutdeparting from the spirit of the invention. For instance, the actionscan be performed in a differing order or actions can be added, deletedor modified. Also, the term “coupled” and variations thereof describeshaving a communications path between two elements and does not imply adirect connection between the elements with no interveningelements/connections between them. All of these variations areconsidered a part of the specification.

In the accompanying figures and following detailed description of thedisclosed embodiments, the various elements illustrated in the figuresare provided with two or three digit reference numbers. With minorexceptions, the leftmost digit(s) of each reference number correspond tothe figure in which its element is first illustrated.

DETAILED DESCRIPTION

In accordance with one or more embodiments of the present invention,customer profiling that takes into account impacts caused by earlyproduct programs is provided. As used herein the terms “early productprogram” and “special agreement program” are used interchangeably torefer to a program where a customer, or client, receives a product (oran update to a product) prior to the product (or the update to theproduct) being generally available. In the computer industry, earlyproduct programs can be in place for hardware, software, firmware, or acombination of two or more of hardware, software and firmware. Examplesof early product programs include, but are not limited to beta testprograms, early support programs, early ship programs, and early adopterprograms. Early product programs can create a big variation in thehistory, transactions, workloads, and culture of a customer. Thevariation can be so great that a special agreement program can impactthe customer profiling performed on the customer and can even cause anincorrect profile of the customer due to the culture of early programswhere feedback about a product as well as an increased number of issuesare expected. One or more embodiments of the present invention can beutilized to recognize the different characteristics of special productprogram scenarios when compared to typical business as usual (BAU)scenarios where a customer obtains a product after it is generallyavailable to the public.

Examples are described herein that relate to the computer industry wherethe products include computer hardware, software, and firmware. Productscan also include new feature deployment of enhancements to existingproducts as well as fixes, or patches, to existing products to correctdefects. Embodiments are not limited to computer products, asembodiments can be utilized by any industry which requires producttesting with a set of customers. Embodiments can be utilized forproducts such as, but not limited to computer products, retail storestrategies, marketing programs, and material science programs.

The term “customer” is used herein to refer to a recipient of a producteither during an early product program or in a BAU manner. Aa usedherein, the term “variable” refers to elements of an early productprogram that are defined, for example, in contractual agreements thatdescribe the early product program such as, but not limited to: generalavailability date, announcement date, installation date, and warrantydata.

As used herein, the term “customer profile” refers to information abouta customer such as, but not limited to: name, contact person(s),business industry, country, system class, customer satisfaction level,likely date of next sale of particular products, and warranty expirationdates. Contents of the customer profile can be derived or sourced fromcustomer systems data which includes information about current productsof the customer, and from customer history data that includes purchasedates and issues related to or reported by the customer. For example,the customer satisfaction in the customer profile can be derived basedon the number of issues within a selected period of time that arecontained in the customer history data. The customer profile can be usedby a vendor for marketing and product support purposes. The customerprofile can further be used for estimating sales predictions and forrecruiting customers for future early product programs.

In accordance with one or more embodiments of the present invention, theimpact(s) of early product programs are analyzed and taken into accountin customer profiles so that customer profiles are not incorrectlyskewed by the customer participating in an early product program. Earlyproduct program variables that can affect a customer profile aredetermined, and customer profiles for customers participating in earlyproduct programs are created or modified based on the identifiedvariables so that they reflect a more accurate view of the customer.

One or more embodiments of the present invention can be used todetermine and define variables related to early product programs and tocreate a model that is applied for customer profiling. Pre-generalavailability (GA) variables are examined and it is determined whetherthey have an impact on the customer profiling. There can be certainearly product program scenarios that can have a significant impact ontypical customer profiling. One or more embodiments of the presentinvention can be used to make customer profiling more accurate bycreating a system to determine variables for customer product programsdynamically and then by creating a correlation model to predict theimpact of some of the special scenarios encountered during early productprograms on customer profiling. The system can analyze issues reportedby the customer and search for events or actions that overlap thoseissues to see if there are any correlations that affected those issuesbased on an early product program agreement. The system can determinethose variables and adjust the customer profile accordingly.

In general, relations and expectations of customers participating inearly product programs, where they are using a product prior to theproduct being generally available, can be very different from a customerthat is receiving a product in a BAU manner (e.g., after GA of theproduct). Some of the issues described, for example, in problemmanagement reports (PMRs), in the early product program timeframe may bequite different from the typical customer issues after the product isgenerally available. In early product programs, customers may expectsome issues such as, but not limited to disruptions, lower performance,and restrictions. In accordance with one or more embodiments of thepresent invention described herein, customer profiles are adjusted toflag, remove, or lessen the impact of these expected issues.

The relationship between workloads, transactions, issues, and culturefor pre-GA systems and post-GA systems can greatly differ depending onthe customer and the program scenario. As used herein, the term“culture” refers to customer expectations. The terms of a specialagreement often set customer expectations differently than the terms ofan agreement that accompanies a BAU purchase of a product. For example,a customer participating in an early product program may expect a longeramount of elapsed time to fix issues and/or a larger number of issues tobe encountered when compared to a product that is GA. Thus, customersthat participate in early product programs often have a more relaxedculture than BAU customers.

One or more embodiments of the present invention can be used todetermine the characteristics of what makes a system GA (e.g., availableto the public in a BAU manner) versus pre-GA to determine the variablesrelated to the early product program, and to use these characteristicsto create a more accurate customer profile. Determining thecharacteristics, or variables, can be performed based, for example, onlegal agreements relating to the early product program, and/or weeklylogs of events occurring during the early product programs (e.g., storedin a customer history file). The system can also identify anomalies inthe pre-GA system that can affect the view of the overall customerprofile. As long as the system can understand the variables thatconstitute the contractual agreements and the culture of the earlyproduct programs, the system can make a determination of whether thesevariables have an accurate effect on customer profiling.

There are contemporary systems that perform customer profiling. However,they do not take into account the impact of products that are receivedprior to GA. The nature and variables for early product programs canvary greatly depending on the program, the contractual agreement(s), andvalidation data between the company selling the product and theircustomers. One of more embodiments of the present invention describedherein can identify these variables which will later be used to analyzethe customer scenarios to determine if there are any predicativepatterns that will impact the customer profiling.

Turning now to FIG. 1, a block diagram 100 that depicts issuesidentified in a customer profile of a customer who has participated inan early product program is generally shown in accordance with one ormore embodiments of the present invention. In the example shown in FIG.1, “customer x” participated in an early support program starting attime 102 for computer hardware that included “machine type 2965z13hardware.” The contract for the special agreement program allowed forthe company providing the product to ship the hardware to “customer x”two months ahead of GA 104. However, the agreement also allowed thiscustomer to continue the use of the hardware sixty days post GA 106 andthen to return to their usual BAU process after sixty days. The sixtydays post GA is a key variable in this example because these machinesare many times not at the mandatory ship levels (MSLs) (e.g., softwareis not at specified version levels) so the issues and history related tothis particular machine may not reflect an accurate picture of what thecustomer is facing during the typical work. Many customers accept theterms and conditions for early product programs with the understandingthat they may have more issues than usual along the way (depending onthe program and agreements). One or more embodiments of the presentinvention can be utilized to understand the variable in this scenarioand when doing customer profiling, if there is any specific situationduring those sixty days, it can understand that the customer may not beunder typical circumstances. Sixty days is an example of a time frameand any other time frame can be specified by a special agreementprogram.

For example, as shown in FIG. 1, pre-GA order data set 108 includes datapoints (e.g., issues) that fall after GA 104 that should be analyzed todetermine if any of them have an impact on customer profiling caused bybeing in the early support program. The effect of these data points canbe flagged or eliminated from the real-order data set 110. The examplein FIG. 1 is a single customer and a single early product program. Theanalysis can become much more complicated when a customer is involved inmultiple overlapping early product programs. One or more embodiments ofthe present invention can be utilized to analyze impacts of multipleearly product programs on a single customer profile.

The variables in the example shown in FIG. 1 can be sourced from thecontract and/or one or more repositories. The variables can include, butare not limited to: early support program entry, early support programinstall, announcement data, GA data, early support program exit date,early support program exit criteria, hardware/firmware/softwaremandatory ship levels (MSLs), and problem management report (e.g.,issue) history for this time period.

One or more embodiments of the present invention can programmaticallyextract, from a contract or other document describing the early supportprogram, that a key variable is “60 days post GA”. Any issues (i.e.,problem management reports) with the product post sixty days after GAcan fall under special situation and will not be considered BAU forcustomer profiling.

Turning now to FIG. 2, a block diagram 200 of a computer system forcustomer profiling that takes into account impacts of early productprograms is generally shown in accordance with one or more embodimentsof the present invention. The computer system shown in FIG. 2 includesprofile filtering logic 210 for performing the processing describedherein. It also includes a beta/early program agreements repository 202,a customer profile repository 204, a customer systems repository 206,and a customer history repository 208 which are input to the profilefiltering logic 210 for performing the processing described herein.

In accordance with one or more embodiments of the present invention, theprofile filtering logic 210 determines the characteristics of what makesa system GA (e.g., for a BAU process) after the customer hasparticipated in an early product program for the product. For example, acomputer processor may need to have hardware, software, and firmware ata specified MSL level. In addition, depending on the contents of thecontract for the early product program, characteristics can includespecific dates such as, but not limited product announcement data and/orGA date. In addition, a code that indicates installation of a GA productcan also be used to differentiate the state of that product.

The customer profile repository can include data such as, but notlimited to current customer name, business name, industry, country, andcustomer satisfaction. The customer systems repository 206 can includedata such as, but not limited to current systems installed at thecustomer location(s), hardware/software/firmware versions of thesystems, and competitor systems installed at the customer location(s).The customer history repository 208 can include historical data such as,but not limited to workload history, purchase history, and issueshistory. The beta/early program agreements repository 202 can includethe special agreements that describe the terms of the early productprograms The special agreements can include data such as, but notlimited to descriptions of a time window for upgrades; windows for extracapacity, extra memory, and extra processors; specific dates forworkloads; upgrades; and warranties.

The profile filtering logic 210 can create a set of variables based atleast in part on the definition and contractual agreements in thebeta/early program agreements repository 202. For example: the profilefiltering logic 210 can create variables for the GA date, theannouncement date, installation date, MSLs, reconciliation date,warranty data, and exit date from the early product program. Inaccordance with one or more embodiments of the present invention, thevariables are extracted by a smart, or question answering computersystem, such as Watson™ from IBM. The question and answering computersystem can be used to perform syntax analysis to extract data when thereis a special agreement between two parties to read and understand theterms of the contract. In this manner, a smart system can generateflags, or variables to be used for determining impacts of the specialagreement program on a client profile.

The profile filtering logic 210 can use the set of variables to create adynamic correlation model of the above data along with the beta/earlyprogram variables for a specific customer. The output of this model caninclude customer profile rules that are used to determine if there areany predictive patterns, trends, outliers, classifications that can beused to adjust customer profiles of those customers that areparticipating for the beta/early programs. In this manner, differencesbetween pre-GA products and BAU products are identified and accountedfor in customer profiling so that a customer profile shows an accurateprofile of the customer.

The components shown in FIG. 2 can be located in one or more differentgeographic locations and connected via one or more networks. Forexample, portions of the profile filtering logic 210 can be executed onone or more different processors in one or more different locations. Inaddition, the beta/early program agreements repository 202, customerprofile repository 204, customer systems repository 206, and customerhistory repository 208 can be physically stored in one or more storagedevices in one or more geographic locations.

Turning now to FIG. 3, a flow diagram 300 for customer profiling thattakes into account impacts of early product programs is generally shownin accordance with one or more embodiments of the present invention. Theprocessing shown in FIG. 3 can be performed by computer instructionsexecuted by a processor implementing the profile filtering logic 210shown in FIG. 2.

At block 302, a customer profile for a customer is received, oraccessed, for example, from the customer profile repository 204. Thecustomer profile can also include data from the customer systemsrepository 206 and the customer history repository 208. At block 304, aspecial agreement that describes an early product program that thecustomer is participating in is received, and at block 306 variables ofthe early product program are extracted from the special agreement. Thespecial agreement can be stored, for example, in the beta/early programagreements repository 202. In accordance with one or more embodimentsthe variables are extracted using text analytics software or questionanswering software as described above.

At block 308, rules are created based at least in part on the extractedvariables. In accordance with one or more embodiments, a dynamiccorrelation model is generated based on the extracted variables. Theoutput of the model includes customer profile rules that are applied tothe customer profile at block 310 and the customer profile is updated atblock 312. Examples of rules include, but are not limited to: flag (orremove) issues related to a particular product under a special agreementprogram between specified dates; and flag (or remove) issues betweenspecified dates of products that interface with a particular productunder a special agreement program.

The profiles are used to determine if there are any predictive patterns,trends, outliers, classifications that should be adjusted in customerprofiles of those customers that are participating in an early productprogram. In some special agreement programs, the agreements may varybetween customers while in other special agreement programs allcustomers may have the same terms in their contracts. When theagreements between customers vary the set of variables extracted by thesmart engine will vary. One or more embodiments of the present inventioncan be used to determine when the data is causing a biased or unbiasedcustomer profile and can then create a correlation model to adjust theskewing based on a special agreement program(s) in place with thecustomer.

At block 314, other customers that are participating in the same earlyproduct program with the same terms are identified. At block 316, therules generated at block 310 are applied to the other customers and atblock 318 their customer profiles are updated. In this manner, blocks304, 306, and 306 only need to be performed once for each unique earlyproduct program agreement.

Turning now to FIG. 4, a block diagram of a computer system 400 forimplementing some or all aspects of customer profiling that takes intoaccount impacts of early product programs is generally shown accordingto one or more embodiments of the present invention. The processingdescribed herein may be implemented in hardware, software (e.g.,firmware), or a combination thereof. In an exemplary embodiment, themethods described may be implemented, at least in part, in hardware andmay be part of the microprocessor of a special or general-purposecomputer system 400, such as a mobile device, personal computer,workstation, minicomputer, or mainframe computer.

In an exemplary embodiment, as shown in FIG. 4, the computer system 400includes a processor 405, memory 412 coupled to a memory controller 415,and one or more input devices 445 and/or output devices 447, such asperipherals, that are communicatively coupled via a local I/O controller435. These devices 447 and 445 may include, for example, a printer, ascanner, a microphone, and the like. A conventional keyboard 450 andmouse 455 may be coupled to the I/O controller 435. The I/O controller435 may be, for example, one or more buses or other wired or wirelessconnections, as are known in the art. The I/O controller 435 may haveadditional elements, which are omitted for simplicity, such ascontrollers, buffers (caches), drivers, repeaters, and receivers, toenable communications.

The I/O devices 447, 445 may further include devices that communicateboth inputs and outputs, for instance disk and tape storage, a networkinterface card (NIC) or modulator/demodulator (for accessing otherfiles, devices, systems, or a network), a radio frequency (RF) or othertransceiver, a telephonic interface, a bridge, a router, and the like.

The processor 405 is a hardware device for executing hardwareinstructions or software, particularly those stored in memory 412. Theprocessor 405 may be a custom made or commercially available processor,a central processing unit (CPU), an auxiliary processor among severalprocessors associated with the computer system 400, a semiconductorbased microprocessor (in the form of a microchip or chip set), amicroprocessor, or other device for executing instructions. Theprocessor 405 can include a cache such as, but not limited to, aninstruction cache to speed up executable instruction fetch, a data cacheto speed up data fetch and store, and a translation look-aside buffer(TLB) used to speed up virtual-to-physical address translation for bothexecutable instructions and data. The cache may be organized as ahierarchy of more cache levels (L1, L2, etc.).

The memory 412 may include one or combinations of volatile memoryelements (e.g., random access memory, RAM, such as DRAM, SRAM, SDRAM,etc.) and nonvolatile memory elements (e.g., ROM, erasable programmableread only memory (EPROM), electronically erasable programmable read onlymemory (EEPROM), programmable read only memory (PROM), tape, compactdisc read only memory (CD-ROM), disk, diskette, cartridge, cassette orthe like, etc.). Moreover, the memory 412 may incorporate electronic,magnetic, optical, or other types of storage media. Note that the memory412 may have a distributed architecture, where various components aresituated remote from one another but may be accessed by the processor405.

The instructions in memory 412 may include one or more separateprograms, each of which comprises an ordered listing of executableinstructions for implementing logical functions. In the example of FIG.4, the instructions in the memory 412 include a suitable operatingsystem (OS) 411. The operating system 411 essentially may control theexecution of other computer programs and provides scheduling,input-output control, file and data management, memory management, andcommunication control and related services.

Additional data, including, for example, instructions for the processor405 or other retrievable information, may be stored in storage 427,which may be a storage device such as a hard disk drive or solid statedrive. The stored instructions in memory 412 or in storage 427 mayinclude those enabling the processor to execute one or more aspects ofthe dispatch systems and methods of this disclosure.

The computer system 400 may further include a display controller 425coupled to a display 430. In an exemplary embodiment, the computersystem 400 may further include a network interface 460 for coupling to anetwork 465. The network 465 may be an IP-based network forcommunication between the computer system 400 and an external server,client and the like via a broadband connection. The network 465transmits and receives data between the computer system 400 and externalsystems. In an exemplary embodiment, the network 465 may be a managed IPnetwork administered by a service provider. The network 465 may beimplemented in a wireless fashion, e.g., using wireless protocols andtechnologies, such as WiFi, WiMax, etc. The network 465 may also be apacket-switched network such as a local area network, wide area network,metropolitan area network, the Internet, or other similar type ofnetwork environment. The network 465 may be a fixed wireless network, awireless local area network (LAN), a wireless wide area network (WAN) apersonal area network (PAN), a virtual private network (VPN), intranetor other suitable network system and may include equipment for receivingand transmitting signals.

Systems and methods for customer profiling that takes into accountimpacts of early product programs as described herein can be embodied,in whole or in part, in computer program products or in computer systems400, such as that illustrated in FIG. 4.

Various embodiments of the invention are described herein with referenceto the related drawings. Alternative embodiments of the invention can bedevised without departing from the scope of this invention. Variousconnections and positional relationships (e.g., over, below, adjacent,etc.) are set forth between elements in the following description and inthe drawings. These connections and/or positional relationships, unlessspecified otherwise, can be direct or indirect, and the presentinvention is not intended to be limiting in this respect. Accordingly, acoupling of entities can refer to either a direct or an indirectcoupling, and a positional relationship between entities can be a director indirect positional relationship. Moreover, the various tasks andprocess steps described herein can be incorporated into a morecomprehensive procedure or process having additional steps orfunctionality not described in detail herein.

The following definitions and abbreviations are to be used for theinterpretation of the claims and the specification. As used herein, theterms “comprises,” “comprising,” “includes,” “including,” “has,”“having,” “contains” or “containing,” or any other variation thereof,are intended to cover a non-exclusive inclusion. For example, acomposition, a mixture, process, method, article, or apparatus thatcomprises a list of elements is not necessarily limited to only thoseelements but can include other elements not expressly listed or inherentto such composition, mixture, process, method, article, or apparatus.

Additionally, the term “exemplary” is used herein to mean “serving as anexample, instance or illustration.” Any embodiment or design describedherein as “exemplary” is not necessarily to be construed as preferred oradvantageous over other embodiments or designs. The terms “at least one”and “one or more” may be understood to include any integer numbergreater than or equal to one, i.e. one, two, three, four, etc. The terms“a plurality” may be understood to include any integer number greaterthan or equal to two, i.e. two, three, four, five, etc. The term“connection” may include both an indirect “connection” and a direct“connection.”

The terms “about,” “substantially,” “approximately,” and variationsthereof, are intended to include the degree of error associated withmeasurement of the particular quantity based upon the equipmentavailable at the time of filing the application. For example, “about”can include a range of ±8% or 5%, or 2% of a given value.

For the sake of brevity, conventional techniques related to making andusing aspects of the invention may or may not be described in detailherein. In particular, various aspects of computing systems and specificcomputer programs to implement the various technical features describedherein are well known. Accordingly, in the interest of brevity, manyconventional implementation details are only mentioned briefly herein orare omitted entirely without providing the well-known system and/orprocess details.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Java, Smalltalk, C++ or the like,and conventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

What is claimed is:
 1. A method comprising: executing, by a processor, aderivation process to derive a first customer profile for a customerbased on customer history data of the customer, the customer historydata comprising workload history data, purchase history data, and issueshistory data; storing, by the processor, the first customer profile asthe customer profile for the customer; identifying, by the processor,that the customer received a product as part of an early productprogram; and based on the identifying: accessing, by the processor, adocument that describes the early product program; extracting, by theprocessor, variables of the early product program based at least in parton content of the document, the extracting comprising performing textanalytics on the content of the document; creating, by the processor,customer profile rules based at least in part on the extractedvariables; modifying, by the processor the derivation process to derivean updated customer profile for the customer that takes into account anyimpacts to the first customer profile caused by the early productprogram, the modified derivation process based on the customer historyof the customer and on the created customer profile rules; andexecuting, by the processor, the modified derivation process to derivean updated customer profile, the executing the modified derivationprocess comprising: executing the derivation process to derive the firstcustomer profile; applying the customer profile rules to the firstcustomer profile, the applying comprising identifying issues in thefirst customer profile that relate to the customer participating in theearly product program, at least one of the identified issues related toa product other than the product received as part of the early productprogram; updating the first customer profile based at least in part onthe applying, the updating comprising flagging the identified issues asbeing related to the early product program; and storing the updatedfirst customer profile as the customer profile for the customer.
 2. Themethod of claim 1, further comprising: identifying an other customerthat received a product as part of the early product program; applyingthe customer profile rules to a customer profile of the other customer,the applying comprising identifying issues in the customer profile ofthe other customer relating to the early product program; and updatingthe customer profile of the other customer based at least in part on theapplying the customer profile rules to a customer profile of the othercustomer, the updating the customer profile of the other customercomprising flagging the identified issues as being related to the earlyproduct program.
 3. The method of claim 1, wherein the early productprogram is selected from the group consisting of a beta test program, anearly support program, an early ship program, and an early adopterprogram.
 4. The method of claim 1, wherein the variables include a daterange of the early product program.
 5. The method of claim 1, whereininput to the applying includes the issues history data.
 6. The method ofclaim 1, wherein the creating customer profile rules includes creating acorrelation model based at least in part on the extracted variables. 7.The method of claim 1, wherein the updating further comprises removingthe identified issues from the updated first customer profile.
 8. Asystem comprising: a memory having computer readable instructions; andone or more processors for executing the computer readable instructions,the computer readable instructions controlling the one or moreprocessors to perform operations comprising: executing a derivationprocess to derive a first customer profile for a customer based oncustomer history data of the customer, the customer history datacomprising workload history data, purchase history data, and issueshistory data; storing the first customer profile as the customer profilefor the customer; identifying that the customer received a product aspart of an early product program; based on the identifying: accessing adocument that describes the early product program; extracting variablesof the early product program based at least in part on content of thedocument, the extracting comprising performing text analytics on thecontent of the document; creating customer profile rules based at leastin part on the extracted variables; modifying the derivation process toderive an updated customer profile for the customer that takes intoaccount any impacts to the first customer profile caused by the earlyproduct program, the modified derivation process based on the customerhistory of the customer and on the created customer profile rules;executing the modified derivation process to derive an updated customerprofile, the executing the modified derivation process comprising:executing the derivation process to derive the first customer profile;applying the customer profile rules to the customer profile, theapplying comprising identifying issues in the first customer profilethat relate to the customer participating in the early product program,at least one of the identified issues related to a product other thanthe product received as part of the early product program; updating thecustomer profile of the customer based at least in part on the applying,the updating comprising flagging the identified issues as being relatedto the early product program; and storing the updated first customerprofile as the customer profile for the customer.
 9. The system of claim8, wherein the operations further comprise: identifying an othercustomer that received a product as part of the early product program;applying the customer profile rules to a customer profile of the othercustomer, the applying comprising identifying issues in the customerprofile of the other customer relating to the early product program; andupdating the customer profile of the other customer based at least inpart on the applying the customer profile rules to a customer profile ofthe other customer, the updating the customer profile of the othercustomer comprising flagging the identified issues as being related tothe early product program.
 10. The system of claim 8, wherein the earlyproduct program is selected from the group consisting of a beta testprogram, an early support program, an early ship program, and an earlyadopter program.
 11. The system of claim 8, wherein the variablesinclude a date range of the early product program.
 12. The system ofclaim 8, wherein input to the applying includes the issues history data.13. The system of claim 8, wherein the creating customer profile rulesincludes creating a correlation model based at least in part on theextracted variables.
 14. The system of claim 8, wherein the updatingfurther comprises removing the identified issues from the updated firstcustomer profile.
 15. A computer program product comprising a computerreadable storage medium having program instructions embodied therewith,the program instructions executable by a processor to cause theprocessor to perform operations comprising: executing a derivationprocess to derive a first customer profile for a customer based oncustomer history data of the customer, the customer history datacomprising workload history data, purchase history data, and issueshistory data; storing the first customer profile as the customer profilefor the customer; identifying that the customer received a product aspart of an early product program; and based on the identifying:accessing a document that describes the early product program;extracting variables of the early product program based at least in parton content of the document, the extracting comprising performing textanalytics on the content of the document; creating customer profilerules based at least in part on the extracted variables; modifying thederivation process to derive an updated customer profile for thecustomer that takes into account any impacts to the first customerprofile caused by the early product program, the modified derivationprocess based on the customer history of the customer and on the createdcustomer profile rules; executing the modified derivation process toderive an updated customer profile, the executing the modifiedderivation process comprising: executing the derivation process toderive the first customer profile; applying the customer profile rulesto the customer profile, the applying comprising identifying issues inthe first customer profile that relate to the customer participating inthe early product program, at least one of the identified issues relatedto a product other than the product received as part of the earlyproduct program; updating the customer profile of the customer based atleast in part on the applying, the updating comprising flagging theidentified issues as being related to the early product program; andstoring the updated first customer profile as the customer profile forthe customer.
 16. The computer program product of claim 15, wherein theoperations further comprise: identifying an other customer that receiveda product as part of the early product program; applying the customerprofile rules to a customer profile of the other customer, the applyingcomprising identifying issues in the customer profile of the othercustomer relating to the early product program; and updating thecustomer profile of the other customer based at least in part on theapplying the customer profile rules to a customer profile of the othercustomer, the updating the customer profile of the other customercomprising flagging the identified issues as being related to the earlyproduct program.
 17. The computer program product of claim 15, whereinthe early product program is selected from the group consisting of abeta test program, an early support program, an early ship program, andan early adopter program.
 18. The computer program product of claim 15,wherein the variables include a date range of the early product program.19. The computer program product of claim 15, wherein input to theapplying includes the issues history data.
 20. The computer programproduct of claim 15, wherein the creating customer profile rulesincludes creating a correlation model based at least in part on theextracted variables.